Phoenix

Phoenix is an open-source AI observability platform designed for experimentation, evaluation, and troubleshooting. It provides:

Tracing - Trace your LLM application’s runtime using OpenTelemetry-based instrumentation.
Evaluation - Leverage LLMs to benchmark your application’s performance using response and retrieval evals.
Datasets - Create versioned datasets of examples for experimentation, evaluation, and fine-tuning.
Experiments - Track and evaluate changes to prompts, LLMs, and retrieval.
Playground- Optimize prompts, compare models, adjust parameters, and replay traced LLM calls.
Prompt Mangement- Manage and test prompt changes systematically using version control, tagging, and experimentation.

Phoenix is vendor and language agnostic with out-of-the-box support for popular frameworks (🦙LlamaIndex, 🦜⛓LangChain, Haystack, 🧩DSPy, 🤗smolagents) and LLM providers (OpenAI, Bedrock, MistralAI, VertexAI, LiteLLM, and more). For details on auto-instrumentation, check out the OpenInference project.

Phoenix runs practically anywhere, including your local machine, a Jupyter notebook, a containerized deployment, or in the cloud.

Installation

Install Phoenix via pip or conda

pip install arize-phoenix

Phoenix container images are available via Docker Hub and can be deployed using Docker or Kubernetes.

Packages

The arize-phoenix package includes the entire Phoenix platfom. However if you have deployed the Phoenix platform, there are light-weight Python sub-packages and TypeScript packages that can be used in conjunction with the platfrom.

Subpackages

Package	Language	Description
arize-phoenix-otel	Python	Provides a lightweight wrapper around OpenTelemetry primitives with Phoenix-aware defaults
arize-phoenix-client	Python	Lightweight client for interacting with the Phoenix server via its OpenAPI REST interface
arize-phoenix-evals	Python	Tooling to evaluate LLM applications including RAG relevance, answer relevance, and more
@arizeai/phoenix-client	JavaScript	Client for the Arize Phoenix API
@arizeai/phoenix-mcp	JavaScript	MCP server implementation for Arize Phoenix providing unified interface to Phoenix’s capabilities

Tracing Integrations

Phoenix is built on top of OpenTelemetry and is vendor, language, and framework agnostic. For details about tracing integrations and example applications, see the OpenInference project.

Python Integrations

Integration	Package	Version Badge
OpenAI	`openinference-instrumentation-openai`
OpenAI Agents	`openinference-instrumentation-openai-agents`
LlamaIndex	`openinference-instrumentation-llama-index`
DSPy	`openinference-instrumentation-dspy`
AWS Bedrock	`openinference-instrumentation-bedrock`
LangChain	`openinference-instrumentation-langchain`
MistralAI	`openinference-instrumentation-mistralai`
Guardrails	`openinference-instrumentation-guardrails`
VertexAI	`openinference-instrumentation-vertexai`
CrewAI	`openinference-instrumentation-crewai`
Haystack	`openinference-instrumentation-haystack`
LiteLLM	`openinference-instrumentation-litellm`
Groq	`openinference-instrumentation-groq`
Instructor	`openinference-instrumentation-instructor`
Anthropic	`openinference-instrumentation-anthropic`
Smolagents	`openinference-instrumentation-smolagents`

JavaScript Integrations

Integration	Package	Version Badge
OpenAI	`@arizeai/openinference-instrumentation-openai`
LangChain.js	`@arizeai/openinference-instrumentation-langchain`
Vercel AI SDK	`@arizeai/openinference-vercel`
BeeAI	`@arizeai/openinference-instrumentation-beeai`

Platforms

Phoenix has native integrations with LangFlow, LiteLLM Proxy, and BeeAI.

Community

Join our community to connect with thousands of AI builders.

🌍 Join our Slack community.
📚 Read our documentation.
💡 Ask questions and provide feedback in the #phoenix-support channel.
🌟 Leave a star on our GitHub.
🐞 Report bugs with GitHub Issues.
𝕏 Follow us on 𝕏.
🗺️ Check out our roadmap to see where we’re heading next.

Breaking Changes

See the migration guide for a list of breaking changes.

Copyright, Patent, and License

Portions of this code are patent protected by one or more U.S. Patents. See the IP_NOTICE.

This software is licensed under the terms of the Elastic License 2.0 (ELv2). See LICENSE.

Installation